Literature DB >> 10898296

Quantitative vascularity of breast masses by Doppler imaging: regional variations and diagnostic implications.

C M Sehgal1, P H Arger, S E Rowling, E F Conant, C Reynolds, J A Patton.   

Abstract

Seventy-four biopsy proven breast masses were imaged by color and power Doppler imaging to evaluate vascular pattern of malignant and benign breast masses. The images were analyzed for vascularity. The measurements were made over the entire mass as well as regionally at its core, at its periphery, and in the tissue surrounding it. The surgical specimens were analyzed for microvessel density. The diagnostic performance of Doppler sonographic vascularity indices was evaluated by receiver operating characteristic analysis. The malignant masses were 14 to 54% more vascular than the benign masses. Both types of masses were more vascular by ultrasonography than the tissue surrounding them. Whereas benign masses were 2.2 times more vascular than the surrounding tissue, the malignant masses were 5.0 times more vascular. In a subset of patients the regional vascularity at the core, periphery, and surrounding tissue by Doppler imaging exhibited a strong correlation (R2 > 0.9) with the corresponding histologic microvessel density measurements. Although the malignant masses exhibited a strong gradient in vascularity, core > periphery > surrounding tissue, the benign masses had relatively uniform distribution of vascularity. The area under the receiver operating characteristic curve (A(Z)) for the Doppler indices ranged from 0.56 +/- 0.07 to 0.65 +/- 0.07. A nonlinear analysis including age-specific values of Doppler indices improved the diagnostic performance to A(Z) = 0.85 +/- 0.06. In conclusion, quantitative Doppler imaging when used in combination with a nonlinear rule-based approach has the potential for differentiating between malignant and benign masses.

Entities:  

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Year:  2000        PMID: 10898296     DOI: 10.7863/jum.2000.19.7.427

Source DB:  PubMed          Journal:  J Ultrasound Med        ISSN: 0278-4297            Impact factor:   2.153


  19 in total

Review 1.  A review of breast ultrasound.

Authors:  Chandra M Sehgal; Susan P Weinstein; Peter H Arger; Emily F Conant
Journal:  J Mammary Gland Biol Neoplasia       Date:  2006-04       Impact factor: 2.673

2.  Quantitative analysis of vascular heterogeneity in breast lesions using contrast-enhanced 3-D harmonic and subharmonic ultrasound imaging.

Authors:  Anush Sridharan; John R Eisenbrey; Priscilla Machado; Haydee Ojeda-Fournier; Annina Wilkes; Alexander Sevrukov; Robert F Mattrey; Kirk Wallace; Carl L Chalek; Kai E Thomenius; Flemming Forsberg
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2015-03       Impact factor: 2.725

3.  Calibration of diffuse correlation spectroscopy blood flow index with venous-occlusion diffuse optical spectroscopy in skeletal muscle.

Authors:  Zhe Li; Wesley B Baker; Ashwin B Parthasarathy; Tiffany S Ko; Detian Wang; Steven Schenkel; Turgut Durduran; Gang Li; Arjun G Yodh
Journal:  J Biomed Opt       Date:  2015       Impact factor: 3.170

4.  Diagnosis of solid breast tumors using vessel analysis in three-dimensional power Doppler ultrasound images.

Authors:  Yan-Hao Huang; Jeon-Hor Chen; Yeun-Chung Chang; Chiun-Sheng Huang; Woo Kyung Moon; Wen-Jia Kuo; Kuan-Ju Lai; Ruey-Feng Chang
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

5.  Noninvasive optical quantification of absolute blood flow, blood oxygenation, and oxygen consumption rate in exercising skeletal muscle.

Authors:  Katelyn Gurley; Yu Shang; Guoqiang Yu
Journal:  J Biomed Opt       Date:  2012-07       Impact factor: 3.170

6.  Machine learning to improve breast cancer diagnosis by multimodal ultrasound.

Authors:  Laith R Sultan; Susan M Schultz; Theodore W Cary; Chandra M Sehgal
Journal:  IEEE Int Ultrason Symp       Date:  2018-12-20

7.  The disruption of murine tumor neovasculature by low-intensity ultrasound-comparison between 1- and 3-MHz sonication frequencies.

Authors:  Andrew K W Wood; Ralph M Bunte; Heather E Price; Margaret S Deitz; Jeff H Tsai; William M-F Lee; Chandra M Sehgal
Journal:  Acad Radiol       Date:  2008-09       Impact factor: 3.173

8.  Correlation between Blood Flow Signal of Color Flow Imaging and Nottingham Prognostic Index in Patients with Breast Carcinoma.

Authors:  Zhi-Yong Shen; Bing Hu; Ming-Feng Wu
Journal:  Breast Care (Basel)       Date:  2012-04-24       Impact factor: 2.860

9.  The antivascular action of physiotherapy ultrasound on a murine tumor: role of a microbubble contrast agent.

Authors:  Andrew K W Wood; Ralph M Bunte; Jennie D Cohen; Jeff H Tsai; William M-F Lee; Chandra M Sehgal
Journal:  Ultrasound Med Biol       Date:  2007-08-27       Impact factor: 2.998

10.  Epidermal growth factor receptor inhibition modulates the microenvironment by vascular normalization to improve chemotherapy and radiotherapy efficacy.

Authors:  George J Cerniglia; Nabendu Pore; Jeff H Tsai; Susan Schultz; Rosemarie Mick; Regine Choe; Xiaoman Xing; Turgut Durduran; Arjun G Yodh; Sydney M Evans; Cameron J Koch; Stephen M Hahn; Harry Quon; Chandra M Sehgal; William M F Lee; Amit Maity
Journal:  PLoS One       Date:  2009-08-06       Impact factor: 3.240

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